computer modeling in irrigation and drainage -...

Computer Modeling in Irrigation and Drainage

Central Soil Salinity Research Institute, Karnal Haryana, India

International Institute for Land Reclamation and Improvement, (Alterra - ILRI) Wageningen, The Netherlands

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Acharya N.G. Ranga Agricultural University, Hyderabad, Andhra Pradesh, India

Gujarat Agricultural University, Ahmedabad

Gujarat, India " j

Indo-Dutch Network Project (IDNP). 2002. Computer Modeling in Irrigation and Drainage. CSSRI, Karnal and Alterra-ILRI, Wageningen. pp. 56.

Published in 2002 in India by Central Soil Salinity Research Institute, Karnal (India) and Alterra- International Institute for Land Reclamation and Improvement , Wageningen (The Netherlands)

Sponsored by the Ministry of Foreign Affairs of the Netherlands through the Royal Netherlands Embassy, New Delhi and Government of India through the Indian Council of Agricultural Research, New Delhi

The sponsoring organisations and participating institutions / universities and project participants assume no liability for any losses resulting from the use of this report.

Cover print : Intech Graphics, #5, “Ankush Chambers”, Opp Dyal Singh College, Karnal-132 001, Tel. 0184-2271451 E-mail : [email protected]

‘Printed at : Yugantar Prakashan Pvt. Ltd., WH-23 Mayapuri Industrial Area, Phase-I, New Delhi - 64 Phones: 011-25135949,25139018

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PROJECT PARTICIPANTS

Kamal (CSSRI) Coordinating Unit, Haryana, India

Dr. N.K. Tyagi (Director) Dr. S.K. Gupta (Head, IDNP) Dr. O.P. Singh Er. P.S. Kumbhare Dr. S.K. Kamra Dr. R.S. Pandey Dr. P.S. Minhas Dr. R.C. Sharma Dr. O.S. Tomar Dr. K.N. Singh Dr. D.K. Sharma Dr. D.P. Sharma Dr. (Ms) Madhurama Sethi Dr. S.K. Luthra Dr. N.P.S. Yaduvanshi Dr. K. K. Datta Dr. A.K. Mondal Dr. S. K. Ambast Er. M. J. Kalendhonkar

Bapatla (ANGRAU) Cooperating Center, Andhra Pradesh, India

Dr. T.V. Satyanarayana (Chief Scientist) Er. D. Appa Rao Dr. (Mrs.) G.V. Lakshmi Er. G. Arvinda Reddy Er. A. Srinivasulu

’ Er. H.V. Hemakumar Er. (Mrs.) C. Sujini Rao Dr. C.V.Hanumantaiah Er. Ch. Ramesh Babu

Bheemarayanagudi (UASD) Cooperating Center, Karnataka, India

Dr. P. Balakrishnan (Chief Scientist) Dr. G.S. Dasog Er: M.S. Shirahatti Er. H. Rajkumar Er. S.N. Upperi Dr. B.M. Doddamani Er. Y.M. Patil Er. C.B. Meti Dr. V.B.Kuligod Er. G.N. Kulkarni Er. A.M. Benki

Wageningen (ALTERRA-ILRI) The Netherlands

Dr. J. Boonstra (Chief Technical Advisor) . Er. H. P. Ritzema Dr, W. Wolters Er. R. J. Oosterbaan Er. (Mrs) Lyda Res (IAC, Wageningen) Er. A. M. van Lieshout (ITC, Enschede)

Hanumangarh (RAU) Cooperating Center, Rajasthan, India

Dr. A. Chandra (Chief Scientist) Er. A.L. Misra Dr. (Mrs.) S. Rathore Dr. P.S. Shekhawat Er. A.K. Singh Er. J .K. Gaur Er. B.R. Godara Er. R.S. Shekhawat Dr. Hanuman Ram

Bapatla (ANGRAU) Coopted Center, Andhra Pradesh, India

Dr. B. Rajendra Prasad Er. M. Raghu Babu Er. Md. Mujeeb Khan Dr. P.R.K. Prasad Er. Y. Radha Krishna . .

Gangavathi (UASD) Coopted Center, . Karnataka, India

Dr. S.G. Patil Dr. M.V. Manjunatha Er. Manjunatha Hebbara Er. G. Ravi Shankar

d Navsari (GAU) Cooperating Center, Gujarat, India

Dr. S. Raman (Chief Scientist) Er. M.M. Parikh Er. A.N. Lad Er. B.R. Patel Dr. R.G. Patil Dr. N.D. Desai Er. N.G. Savani Dr. P.K. Shrivastava Dr. A.M. Patel Er. N.J. Ahir Er. O.D. Vanparia

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EXECUTIVE SUMMARY

Computer simulation models are known to be the most attractive tools to assess hydrological or environmental situations in irrigated and drained lands. As such, crop-water-environment-models have been increasingly applied to assess the short and long-term impacts of water management options on the land/water productivity and the environment. In view of the potential of computer modeling application in future, it has been an integral and most important component of the Indo-Dutch Network Project. Since the success of any modeling exercise depends to a great extent on the availability of quality input data, the field experiments planned under the project provided the necessary inputs to calibrate/validate the models.

Four models the SWAP, the UNSATCHEM, the SALTMOD and the SURDEV have been applied. Out of the four, three models have been successfully calibrated and validated at least at one location. The model SALTMOD, on the other hand, has been applied under three different agro-climatic conditions. Excellent results were obtained with SWAP on irrigation management in drained lands, UNSATCHEM for describing solute transport for one-dimensional variably saturated - w-ater flow with multi-component solute transport with major ion equilibrium and kinetic chemistry, SALTMOD for prediction of salt and water balance scenarios in drained lands under varying water management options, and SURDEV for developing guidelines to optimise the irrigation performance. The SWAP and the UNSATCHEM, being physically based models, besides practical applications had strong advantages in understanding the physical processes. It was observed however,.that to extend their use to other sites would require dedicated efforts in assembling the input data. On the other hand, the SALTMOD and the SURDEV are based on simplified concepts and are therefore, less demanding on inputs. With intensive and extensive application of these and other computer simulation models, it is believed that firmer recommendations would emerge to decide upon the full potential of these models for their application in India. Without doubt, computer simulation models being powerful tools, their application for planning purposes in the irrigation commands of India would be quite common.

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CONTENTS

1. GENERAL BACKGROUND

2. THE PROJECT

2.1 Project Outline

2.2 Implementing Agencies

2.3 Reporting

/ 3. THIS REPORT

4. SOIL-WATER-ATMOSPHERE-PLANT MODELING: WESTERN YAMUNA CANAL COMMAND (CSSRI)

4.1 Introduction

4.2 Study Site

4.3 Model Calibration and Validation

4.3.1 Calibration

4.3.2 Validation

4.4 Scenario Building

4.4.1 Short-term scenario

4.4.2 Long-term scenarios

4.5 Conclusions and Recommendations

5. SOLUTE-TRANSPORT MODELLING USING UNSATCHEM (CSSRI)

5.1

5.2

5.3

5.4

5.5

5.6

Introduction

Basic Features of UNSATCHEM

Water Quality and Study Sites

5.3.1 Hisar experiment

5.3.2 Ludhiana site

Calibration and Validation

5.4.1 SO, breakthrough curves

5.4.2

Scenario Building: Conjunctive Use

Conclusions and Recommendations

Alkali water use on cropped land

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6. SALT AND WATER BALANCE MODELLING: THE KONANKI PILOT AREA (ANGRAU)

6.1 Introduction

6.2 Study Site

6.3 Model Calibration

6.3.1

6.3.2 Calibrating the leaching efficiency

Determining the natural subsurface drainage


6.4.1

6.4.2 Reconstructing the initial situation

6.4.3

6.4.4

6.4.5

Prediction of future soil salinity and depth to water table

Effect of varying drain spacing on root zone salinity

Effect of changes in irrigation water applied on root zone salinity

Effect of drain depth and irrigation water applied on water table


7. DESIGN AND EVALUATION OF SURFACE IRRIGATION METHODS IN SOUTHERN GUJARAT USING SURDEV (GAU)

7.1 Introduction

7.2 Model Parameters

7.3

7.4


SALT AND WATER BALANCE MODELING: THE SEGWA PILOT AREA (GAU)

8.1 Introduction

8.2 Study Site

8.3 Mo'del Calibrationand Validation

Application of BASDEV for Basin Design

Application of FURDEV for Furrow Evaluation

8.

, 8.3.1 Determining the natural subsurface drainage

8.3.2 Calibration of leaching efficiency


8.4.1

8.4.2

Prediction of soil salinity with drainage system

Reconstruction of the initial situation

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8.4.3

8.4.4


Effect of varying drain depth and irrigation water applied on water table


9. SALT AND WATER BALANCE MODELLING: TUNGABHADRA IRRIGATION PROJECT (UASD)

9.1 Introduction

9.2 Study Site

9.3 Model Calibration


9.4.1

9.4.2

9.4.3

9.4.4

Prediction of future soil salinity and depth to water table

Effect of controlled drainage on root zone salinity and water table


Effect of changes in irrigation water applied on root zone salinity


REFERENCES

SYMBOLS USED

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1. GENERAL BACKGROUND

Agriculture is a key sector in India’s economy, contributing about 35% of the Gross Domestic Product and employing 65% of its adult population. Of the total population of over 1000 million, more than 30% live below the poverty line and about 75% live in rural areas, depending directly or indirectly on agriculture. One-third of the agricultural labour force are women and agriculture is the main source of employment for women in rural areas. Annual agricultural growth has been modest at 2.6% per annum over the last 25 years. Development plans of the Government of India (GoI) and State Governments give priority to alleviating poverty and creating employment, particularly / in rural areas. Considerable irrigation potential has been created in India to sustain agricultural production against the vagaries of rainfall that is scarce and unevenly distributed in space and time.

The introduction of irrigated agriculture, however, in arid and semi-arid regions of the country has resulted in the development of the twin problem of waterlogging and soil salinization, with considerable areas either going out of production or experiencing reduced yield. It is estimated that an area of nearly 8.5 million ha is affected by soil salinity and alkalinity, of which about 5.5 million ha in the irrigation canal commands and 2.5 million ha in the coastal areas. The problem of increasing salinity caused by the rise of the water table and the lack of drainage is considered as a major environmental problem that threatens the capital investment in irrigated agriculture and its sustainability.

GoI’s long-term strategy is to stimulate agricultural growth and promote rural development through improved water and land management, enhanced efficiency of irrigation and drainage networks, strengthened research activities, increased attention to environmental protection, and improved rural infrastructure.

Investment programmes, to address these elements and to re-establish growth, are of high priority in the Tenth Five Year Plan of Go1 and State Governments. It is planned to double the food grain production in the next two decades. This can only be achieved through a concerted effort on all fronts including the reclamation of waterlogged salt-affected lands in*all irrigation command areas. Irrigated agriculture will continue to be the mainstay of progress in the Indian agriculture to ensure food and nutritional security through crop diversification.

Joint Completion Report on IDNP Result # 3 “Computer Modeling in Irrigation and Drainage”

2. THEPROJECT

During 1995, the Governments of India and The Netherlands agreed upon collaboration in the Network Operational Research Programme on the Control of Waterlogging and Salinization in irrigated Agricultural Lands. The programme started on 1 November 1995 upon approval by the Government of India through the Side Letter and ended on 30 April 2002.

The programme aimed at the development of appropriate location-specific drainage and reclamation technologies for solving the problems of waterlogging and salinity in canal commahds of India. It also envisaged developing practical survey methods for diagnosis of problems of waterlogging and salinity. Further it aimed at establishing competent Centres in these fields. From here on, the programme is referred to as the Indo-Dutch Network Project for short.

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2.1 Project Outline

The Indo-Dutch Network Project was planned and executed with the use of the Objective Oriented Project Planning (OOPP) technique. Based on the overall p d project objectives, the results and corresponding activities were formulated in a logical framework (Table 1).

The project had four overall objectives:

1. Increase of agricultural production from salt-affected lands through application of proper soil and water management practices along with other agro-techniques

Prevention of deterioration of productive land through adoption of appropriate soil and water management practices ,

Improvement of social-economic conditions of small and marginal farmers of these lands

Developing expertise for handling reclamation projects in India

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3.

4.

From these overall objectives, two Project Objectives were derived:

1. -

Strengthened research capacity of CSSIU and the four State Centres, especially in the field of waterlogging and salinity control

Enhanced awareness on drainage and related water management for the control of waterlogging and soil salinity at State and Central level

2.

The overall and project objectives were translated in eight project fesults (Table 1). For each result an Objectively Verifiable Indicator was formulated to monitor whether the Project achieved the results as planned. This has resulted in a list with means of verification specifymg how the indicators are reported. However, the conditions needed to reach these results were not always within the competence or mandate of the Project, and were therefore considered as outside factors, although with importance for the Project. These conditions, sometimes also referred to as risks but in this project as Important Assumptions, were monitored. The results were translated in a set of activities (Table 2). These activities formed the basis of the research conducted by the participating Network Centres. In the subsequent annual work plans the activities were further specified based on the reported progress.

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Joint Completion Report on IDNP Result ## 3 "Computer Modeling in Irrigation and Drainage"

Table 1. Overall logical framework Indo-Dutch Network Project - objectives and results Objectively verifiable indicators Means of verification Important assumptions

Overall objectives 1 Increase of agricultural production from salt-

affected lands through application of proper soil and water management practices along with other agro-techniques;

2 Prevention of deterioration of productive land through adoption of appropriate soil and water management practices;

3 Improvement of social-economic conditions of small and marginal farmers of these lands;

4. Developing expertise for handling reclamation projects in India.

Project objectives 1 Strengthened research capacity of CSSRI

and the four State Centres, especially in the field of waterlogging and salinity control

2 Enhanced awareness on drainage and related water management for the control of waterlogging and soil salinity at State and Central Level

Results 1. A methodology for identification of

waterlogging and soil salinity conditions using reomote sensing

2. Recommendations on waterlogging and salinity control based on drainage pilot area research

3. Appraisal of irrigation and drainage practices by computer simulations.

4. Improved human resources at CSSRI and the four State Agricultural Universities through training

5. Operational Training Centre at CSSRI

6. Enhanced awareness at State and Central level on the necessity of an agricultural drainage policy

7. Enhanced awareness at farmers' level on improved irrigation and drainage for control of warelogging and salinity

B. Advice on drainage and related water management

By April 2002 CSSRI and the four State Review by experts Centres will have published quality reports on the control of waterlogging and soil salinity Check on relevant By April 2002 there will be ample documents documentary evidence of enhanced awareness on waterlogging and salinity control at village, State and Central level

* Joint report By April 2002 CSSRI ahd the State Centres will have published a joint report with a methodology to identify waterlogging and soil salinity conditions Joint report By April 2002 CSSRI and State Centres will a progress reports have published a joint report on combating waterlogging and soil salinity * Joint report By April 2002 CSSRI and at least 2 State Progress reports Centres will have published a joint report on the appraisal of irrigation and drainage practices by computer simulations tested in the drainage pilot areas * Progress Reports By April 2002, 50% of the project staff and Interviews 100% of the scientific staff will have parti- Back-to-office cipated in a training activity reports

* Field check By April 2002 CSSRI will have developed 3 * Review of curricula training modules and conducted at least 2 * Course evaluation national training courses in the new training Centre Che k of relevant By April 2002 at least 3 State Governments docu ents will have expressed their willingness to prepare an agricultural drainage policy as documentary evidence Progress repors By April 2002 in at least 2 State Centres a Meeting with Pilot Area Farmers Committees will have farmers ,

been established * Progress reports Bv ADril2002 CSSRI and the State Centres

progress reports

reports

Acceptance of Project results at policy level

Investment in improved water - '

management

Continued support of ICAR and State Agricultural Universities

* Continued involvement of trained staff Involvement of relevant staff available at CSSRI for networking Acceptance of project results by

' end-users (Ministries, farmers, contractors, pipe manufacturers)

have each given at least 20 working days/ year advice to others

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Joint Completion Report on IDNP Result # 3 "Conrputer Modeling in Irrigation and Drainage"

Table 2. Overall logical framework Indo-Dutch Network Project-activities Activities Important assumptions

1.1 1.2 1.3 1.4 1.5

2.1 2.2 2.3 2.4 2.5 2.6 2.7

3.1 3.2 3.3 3.4

4.1 4.2 4.3

5.1 5.2 5.3

5.4

6.1 6.2 6.3

6.4 6.5 6.6

6.7

7.1 7.2 7.3 7.4 7.5 7.6

8.1 8.2 8.3 8.4 8.5

Identify study area Develop physical facilities for remote sensing Develop a methodology Map waterlogged and salt-affected areas Report on methodology and its applicability

Select pilot areas in farmers' fields Conduct a drainage experiment Conduct a water management experiment Conduct a socio-economic study Conduct a cost-benefit analysis of drainage Conduct other related studies Formulate recommendations

Select computer models Acquire physical facilities Conduct computer simulations for diagnosis and prediction Report on the appraisal

Participate in training activities in India Participate in training activities abroad Conduct or participate in in-service training activities

Construct and furnish training centre and hostel Prepare a programme for National Training Courses Develop training modules on - Land Drainage - Management of Problem Soils -.Use of Poor Quality Water for Agriculture Conduct National Training Courses

Train field-level workers on the need for drainage Conduct workshops & seminars on the need for drainage Include officers from interested agencies in the Project Implementation Committees (PIC'S) Prepare and distribute appropriate literature Promote awareness by public relation activities Conduct a desk-study on the institutional and organisational set-up of agricultural drainage in other countries Prepare a.background document for State Agricultural Drainage Policies

Undertake excursions to drainage projects Train extension workers and farmers on drainage '

Conduct farmers' days Prepare and distribute appropriateliterature ,

Involve local farmers in project activities Establish Pilot Area Farmers Committee

Assist others with training courses Assist others with drainage design Advise others on drainage and related water management Advise others on diagnosis and mapping of problem soils Report on the advises rendered

Qualified staff at Centres Timely approval of proposals by the competent authorities

Qualified staff at Centres Timely approval of proposals by the . competent authorities

-: + '0 No climatic catastrophe 0 Full co-operation of the relevant

organisations Full co-operation of farmers

Qualified staff at Centres

Qualified staff at Centres

Qualified staff at CSSRI Identified need for National Training Courses Full co-operation of the relevant organisations

Qualified staff at Centres Co-operation of State and Central organisations

Qualified staff at Centres Full co-operation of farmers

Qualified staff at Centres Requests for advice

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Joint Completion Report on IDNP Result # 3 "Coinputer Modeling in Irrigation a i d Drniizage"

2.2 Implementing Agencies

The Executive Authorities of the Indo-Dutch Network Project were the Indian Council of Agricultural Research (ICAR) and the Royal Netherlands Embassy. (RNE), New Delhi. The implementing agencies of the Indo-Dutch Network Project were:

The Central Soil Salinity Research Institute (CSSRI), Karnal, as coordinating centre (focal point) for the following state centres:

The Acharya N.G. Ranga Agricultural University (ANGRAU), with office facilities at Bapatla.

The University of Agricultural Sciences, Dharwad (UASD), with office facilities at Bheemarayanagudi and Gangavathi

The Gujarat Agricultural University (GAU), with office facilities at Navsari

The Rajasthan Agricultural University (RAU), with office facilities at Hanumangarh

The Supporting Agency from The Netherlands was the International Institute for Land Reclamation and Improvement (Alterra-ILRI), Wageningen.

2.3 Reporting

Several options were considered to bring out the final report of the project. In the end, it was decided to bring out 4 different volumes. While the first three vollimes deal with the Project Results 1 to 3, the fourth volume provides an overview of the accomplishments in the human resource development and establishment of a training centcr (Project Results # 4 and 5). It was decided that the information on activities related to enhanced awareness and advise on drainage rendered by the centers (Project Results # 6 to 8) would form a part of the ifidividual reports that would be brought out by the Network Centres.

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4. SOIL-WATER-ATMOSPHERE-PLANT MODELING: WESTERN YAMUNA CANAL COMMAND (CSSRI)

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4.1 Introduction

Knowledge of water and solute flow in the root zone is essential to assess soil/water conditions and management options to manage land and water in a most-effective manner. Numerical model Soil-Water-Atmosphere-Plant (SWAP) which integrates water flow, solute transport and crop growth was utilised to assess the performance of subsurface drainage activities at Mundlana in Sonepat district. The SWAP model essentially models:

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Solute transport

Heat flow

It includes soil heterogeneity, detailed crop growth parameters, regional drainage at various levels (both surface and horizontal subsurface drainage are included) and water management options. With the addition of. graphic interface, this model seems to be lone of the good models that are now available for simulating salt and water balance in the root*zone.

Water transport through numerical solution of the Richard’s flow equation

4.2 Study Site

Study site is located in the Western Yamuna Canal Command and is a part of the Indo-Gangetic alluvial plain. The selected site has been severely affected by the problems of waterlogging and soil salinity. A brief description of the site follows.

Experimental site is in the Sonepat district of the Haryana State near Gohana. With an average annual rainfall of 550 mm and average potential evapotranspiration at 1650 nun, the area forms a part of the semi-arid region of the state. The study site is flat with gentle slope ranging from 0.1 YO to 0:2 Yo. The soils of the experimental site are sandy-loam in texture in the surface l m layer. The soil textuie is loam between 1 to 5.2 m and below which it is silty clay. The soils were initially saline having salinity as high as 50 dS m-l. The soil salinity decreases after the monsoon but gradually increases during post-monsoon season. Some parts of the fields are also affected by the alkali problem. Water table fluctuates between the soil surface during the monsoon season to a depth of about 1.4m during the summer. Thus, drainage improvement is essential for the reclamation of these lands. The salinity of the groundwater is 22 dS m-l during summer, which also reduces to 14 dS m-l during rainy season as a result of dilution.

A subsurface drainage system was provided on an area of about 8 ha with drains spaced at 50,67 and 84m. The depth of {he drains was kept at 1.75m. Following the installation of drainage system, salts were leached and it was possible to grow crops. The present modeling study has been carried out in an area where sorghum-wheat cropping sequence was followed for a period of 3 years (1990 to 1992-93). The conjunctive use of saline drainage and groundwater was made to irrigate the crops.

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Joint Completion Report on IDNP Result ## 3 “Computer Modeling in lrripfion and Drainage”

4.3 Model Calibration and Validation

4.3.1 Calibration

The data for the 3 agricultural years was used to calibrate and validate the model. The model was calibrated for the agricultural year 1990-91 (one wheat and one sorghum crops including fallow period). A fallow period between last week of August to second week of November was included. The soil physical parameters for the present simulation study are reported in Table 3.

Table 3. Model input data for Van Genuchten - Mualem parameters describing the water retention and unsaturated hydraulic conductivity characteristics

Soil layers Ks (cmld) = (llcm) Ne) Kex0 (-1 I 48.7 0.0213 1.800 -0.400 11 60.0 0.0205 1 .goo -1 .o00

I l l 25.5 0.1820 1.952 -1.400

The data were the same for all the treatments and for the whole study period. At the bottom boundary, the groundwater levels were assigned as per the observed data. The relevant crop characteristics for calibration of the SWAP model are presented in Table 4. The maximum effective root length for the wheat and sorghum were taken as 130 and 150 cm, respectively. Estimated leaf area index of wheat exceeded 1.0 m2/m2 at 7 weeks after sowing and it reached a maximum of 4.4 m2/m2 at 15 weeks after sowing and thereafter rapidly decreaseddue to leaf senescence (Table 4). The leaf area index of sorghum up to 4th week was less than 1 mz/m2 but it showed an increasing trend and c. peak value of 5.6 m2/m2 was recorded at the time of harvesting because crop was harvested for forage (Table 4). The reduction in water uptake by roots due to water and/or salinity stress was also included in the model. The critical pressure head (h) was taken as -400 cm (wheat) and -325 cm (sorghum) for a high evaporative demand of 5 cm/d. At low evaporative demand of 1 cm/d, the (h) amounted -1500 cm for wheat and -2500 cm for sorghum. A brief description of the crop factor, the threshold and the slope follows.

Table 4. Ranges of plant characteristics of sorghum and wheat

Characteristics Sorghum Wheat

Duration (days) Leaf area index (m2/m2) Rooting depth (m) Yield response factor Rooting density distribution Crop factor ECe threshold (dS/m) EC slope (% per dS/m)

77-79 0.05-5.6 0.0-1.5 0.9-1 .o 0.4-1 .O 0-1.28

4.10-8.8 9.5-14.6

155-1 58 0-4.4

0.0-1.3 0.9-1 .o 0.15-1 .O 0-1.36

3.06-4.73 9.3-1 3.2

Joint Completion Report on IDNP Result # 3 "Computer Modeling in lrrigatioii and Drainage"

A two-way approach is adopted to calibrate the daily potential evapotranspiration. In the first step the calculation of reference evapotranspiration is made using Penman-Monteith equation for wet and dry canopy with complete soil cover and potential evaporation rate of wet, bare soil. In the second step, the crop evapotranspiration is calculated using the crop coefficients which were developed at Karnal. The estimated Kc values of wheat measured by lysimeter experiment at Karnal by Frad method during initial, crop development, reproductive and last stages were 0.47, 1.36,1.02 and 0.35 respectively and these values estimated by PanE method were 0.75, 1.30, 1.16 and 0.33 in respective stages. The estimated Kc values calculated by Frad and PanE during initial stage were 1.34 and 2.14 times respectively higher than the FAO Kc values and these values were also 1.56 to 1.82 times higher during crop development stage. This could mainly be due to additional source of energy available from soil heat flux. But in the reproductive phase and at maturity, the average Kc values were identical to the FAO values. The average seasonal Kc value of wheat is slightly higher than the FAO value.

During the sorghum season, the estimated average stage-wise Kc values differ markedly with FAO Kc values in the respective stage except the third stage (reproductive phase). Crop coefficient were in the range of 0.45 to 0.53 in the first stage and average Kc value was lower than the FAO value by 30%. In the second stage, Kc values were in the range of 0.82 to 0.93 and estimated average Kc value during this stage was 13.7% lower than the FAO value. But in the reproductive phase (third stage), the average Kc values were identical to the FAO value. The estimated average Kc value was lower than the FAO Kc value by 32.6% in the last stage. However, the average seasonal Kc value of sorghum was slightly higher than the FAO value. The crop coefficients as actually measured at Karnal were used for the present study.

For the present simulation study, the ECe threshold at which yield reduction starts for different stages ranged from 4.10 to 8.89 ror sorghum and 3.06 to 4.73 for wheat. The ECe slope for the two crops were set at 9.5 to 14.6 for sorghum and 9.3 to 13.2 for wheat. The initial pressure head of

were provided in each compartment, and initial solute concentrations of 3.17,3.08,2.76,3.43 and 3.22 mg/cm" at respective depths were defined. The model predicted salt concentration did match closely with the field observed ECe levels. The predicted values of soil ECc are 11.7,8.8,9.7 and 8.1 dS/m. The predicted values of soil ECe were more closer to observed values when crop was irrigated with groundwater (GW) than canal water (CW). Probably the model simulates more leaching of salts with uniform soil layers when ECeis less than 2 dS/m. A very close agreement between the model estimated soil profile moisture and field measured values for the two water qualities of canal and groundwaters were observed. The nice calibration of the SWAP model is further reflected in close matching of the simulated and measured crop yield (Table 5).

In case of canal water, no reduction in yield has been observed for both the crops. When the crops are irrigated with underground poor quality water, simulated yield reduced to 96 and 61% for sorghum and wheat, respectively. Thus, the difference between field observed and predicted values by the model were only 4 and 6% for respective crops.

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-145.4, -121.9, -101.12, -90.1 and -66.9 cm for 0-15, 15-30, 30-60,60-90 and 90-120 cm respectively , 8 !a!

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Joint Completion Report on IDNP Result ## 3 “Computer Modeling in lrrigation and Drainage”

Table 5. Predicted and observed yield of crops under canal water and groundwater for 1990-91

Crops Years Relative grainlforage yield (%) Predicted Observed Difference

cw GW cw GW cw GW

Sorghum 1990 1 O0 96 1 O0 92 O 4

Wheat 1990-91 1 O0 61 1 O0 67 O 6 I

4.3.2 Validation

The validation study was conducted using data for the remaining 2 years period i.e., 1991-93. The soil, water and plant parameters used in the calibration were kept as such for the validation period. The calibrated profile water salinity could match very closely also during the validation period with the field observed values when crops were irrigated with groundwater (GW), drainage water (DW) and alternative modes of canal and groundwater (AG) and canal and drainage water (AD). The ECe under canal water predicted by model were less than 1 dS/m while observed - salinity were slightly higher than 1 dS/m. The satisfactory validation was further reflected in close matching of soil profile moisture with the measured values for both the canal and groundwater. Finally, the average differences of the model predicted and observed grain yield of both crops were very small (Table 6).

The measured and simulated grain yield of sorghum differed only 2.7 to 4.3 t ha-* (5.7 to 8.7%) during 1991-92 and 1.3 to 3.0 t ha-’ (2.1 to 6.1%) during 1992-93. Similarly, the small differences in wheat yield of 0.17 to 0.29 t ha-’ (3.7 to 6.4%) during 1991-92 and 0.07 to 0.33 t ha-* (1.6 to 7.0%) in 1992-93 were observed. These observations reflect the utility and power of the SWAP-model.

Table 6. Simulated and observed yield (t hal) of crops under different treatments during 1991-92 and 1992-93

I I Treatments Sorghum Wheat

Predicted Observed Difference Predicted Observed Difference

(PI (0) (P-0) (PI (0) (P-0) 1991-92 CW 49.9 49.9 0.00 4.61 4.61 0.00 DW 48.9 44.8 4.10 4.61 4.44 0.17

GW 46.4 43.6 2.70 2.85 2.62 0.23

AD 49.4 45.7 3.71 4.61 4.36 0.25

AG 49.4 45.1 4.30 4.24 3.95 0.29 1992-93 CW 51.2 51.2 0.00 4.74 4.74 0.00 DW 50.1 47.1 3.02 2.74 4.48 0.26

GW 47.1 45.8 1.30 4.32 2.25 0.07

AD 50.6 49.1 1.58 4.74 4.41 0.33

AG 50.6 48.9 1.71 4.31 4.10 0.21

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Joint Completion Report on IDNP Result # 3 "Conzpirter Modeling in lrrigntioii and Drainage"

Short-term irrigation management scenarios are simulated and compared with the simulated results of a reference irrigation scenario, which is based on the results from experiments conducted during 1990-91 to 1991-92 at the same site (Table 7). The recommendations include a pre-sowing irrigation with canal water (ECl,,,=0.36 dS/m) to leach the salts during the initial stage of crop growth and application of more water for leaching. This pre-sowing irrigation with fresh water is essential because the evaporation during the months of May and June is about 10-12 mm/d, which causes salt accumulation in the surface layer. Since sorghum is sensitive to salinity during germination stage, a salt free root zone is needed at this stage. To leach the salt applied with irrigation water, excess application of water is recommended. Since the water in the command is limited, it was . thought to assess the under irrigation scenario as well as a scenario in which saline water is used for irrigation for pre-sowing.

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The quite satisfactory agreement between the model simulation and field observation for various soil, water and crop parameters provided the required confidence in using the successfully calibrated and validated SWAP simulation model for short-term and long-term (two decades or more) scenario building studies.


Whenever water is scarce, whether because of natural shortage or inadequate allocation, farmers adept to this situation by reducing the amount of water applied to make its best possible use. It helps in cutting the non-productive use of water by curtailing evaporation, deep percolation and other losses. On a short-term basis, the marginal impact of water management variables like quantity, quality and its application frequency helps to achieve higher water application efficiency. On the other hand, it is feared that salt accumulation might occur during such situations. Thus, such a scenario might increase soil salinity and adversely affect the crop production in the long- term. Therefore, a study on short and long-term impact of such a scenario on environment degradation is attempted. -.

4.4.1 Short-term Scenario

In the under-irrigation scenario, two possibilities were examined. In both the possibilities the total depth of water applied was decreased from 60 cm to 48 cm (20%) of the reference depth. This was achieved by reducing the depth of each irrigation in one case. In the other, depth of irrigation was adjusted in such a manner that number of post sowing irrigation were reduced from 4 to 3 and was designated as low frequency. In the second scenario, a pre-sowing irrigation of inferior quality of groundwater mixed with canal water is given to wheat crop. The results of seasonal salt and water balance under different scenarios are reported in Tables 8 and 9 while the annual salt . and water balance is reported in Table 10. The initial salt storage in all the scenarios was set at around 142 mg/cm2 such that the impact of the alternate options could be compared.

In case of reference scenario, the wheat crop is over-irrigated than sorghum crop, as indicated by higher change in salt storage during the wheat season (+24.2 and +13.6 mg/cm3, Table 9) compared to sorghum crop (-80.8 and -3.4 mg/cm3, Table 8). When the rainfall is about 423 mm during

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Joint Completion Report on IDNP Result # 3 "Coniputer Modeling iri irrigation and Drainage"

monsoon season (June to September), some salt accumulation was observed in the soil profile with low irrigation frequency or under irrigation scenarios compared with reference scenario. During the winter season (November to March), salt accumulation was higher in reference scenario compared to under or lower irrigation frequency scenarios (Table 9). It is mainly due to higher amount of drainage water (42 cm) applied under reference scenario than the low irrigation frequency or under irrigation scenarios (33 cm).

Table 7. Details of management scenarios in term of quantity (cm), quality (mg/cm2) and frequency of water application

~~~~~ ~

Scenarios Sorghum season (June-August) Wheat season (November-April) Quantity Quality Frequency Quantity Quality Frequency

(mg/cm2) (cm) (mg/cm2) (no.) Pre Post Pre Post Pre Post

Reference i o a 0.28 0.28 1 1 i o a 0.2 5.121 1 4 (60cm) 4.4v

(4acm) 4.48 4.48

Low frequency 8 7 0.28 8.58 1 1 9 a 5.121 5.121 I 3 (48cm) 4.48 4.48

Under irrigation 8 7 0.28 8.58 1 1 7 6.5 5.121 5.121 1 4

* Salinity of water in the first and second year of experiment

Table 8. Seasonal salt and water balance during the sorghum seasons ~~~

Scenarios P(cm) Ip(cm) Tac,(cm) Eac, (cm) DW (cm) DS (mg/cm2) Qbot (cm) Reference 1990-91 50.4 i 8.0 23.6 8.5 -13.2 -80.8 -49.5

1991-92 42.3 i 8.0 21.6 9.2 11.4 -3.4 -17.2

Under-irrigation 1990-91 50.4 15.0 23.6 8.7 -46.2 -37.9 -1 5.5

1991-92 42.3 15.0 21.6 9.2 11.8 16.5 -14.3

Low frequency 1990-91 50.4 15.0 23.6 9.4 -1 3.2 -42.7 -45.2

1991-92 42.3 15.0 21.6 13.7 11.0 21.6 -1 4.3

Table 9. Seasonal salt and water balance during wheat seasons

Scenarios P(cm) Ip(cm) Tac,(cm) Eact (cm) DW (cm) DS (mg/cm2) Q,,, (cm) Reference 1990-91 1 1 .O3 42 25.1 10.6 -6.16 24.2 -23.19

1991-92 8.34 42 21.2 7.2 -0.54 13.6 -22.20

Under-irrigation 1990-91 11 .O3 33 26.1 10.6 -6.63 -8.2 -13.80

1991-92 8.34 33 21.2 7.3 -0.85 13.3 -14.80

Low frequency 1990-91 11 .O3 33 25.2 7.8 8.1 -7.1 -3.70

1991-92 8.34 33 21.2 7.4 -1.23 -5.2 -1 3.52

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Joint Completion Report on IDNP Result # 3 "Compirter Mudelirig in lrrigntiori nrzd Dmirinye"

It may be seen that there is no major build-up of salts even on annual basis (Table 10). Since a large fraction of the water applied goes below the root zone, it takes care of leaching requirement for salt balance (Table 10). The yield and transpiration of sorghum are not affected by the irrigation given under different scenarios (Table 11). In the low irrigation frequency scenario, more salts are leached due to less amount of water taken by plants compared to reference scenario and thus, more water is available for leaching of salts. In the under or low irrigation scenarios, relative ET, transpiration efficiency and evapotranspiration efficiency are more than the reference scenario. Managing salt and water balance by means of changing the irrigation interval or depth is more effective in the wheat (November to April) season than in the sorghum season.

Table 10. Annual salt and water balance for two years under different scenarios

Scenarios P(cm) Ip(cm) Tact (cm) E,=, (cm) DW (cm) DS (mgkm*) Qbot (cm) Reference 1990-91 84.5 60 48.7 28.7 -14.6 -74.4 -78.7

1991-92 58.4 60 42.8 24.4 -0.47 9.23 -49.6 Under-irrigation 1990-91 84.5 48 48.7 28.9 -14.7 ' -0.61 -66.5

1991-92 58.4 48 42.8 24.4 -0.49 26.1 -37.6 Low frequency 1990-91 84.5 48 48.8 24.8 -14.4 -71.3 -67.0

1991-92 58.4 48 42.8 23.9 -0.43 25.2 -38.1 '

Table 11. Crop response indicators under different scenarios

Scenarios Relative Relative Transpiration Evapotranspiration

Sorghum Wheat Sorghum Wheat Sorghum Wheat Sorghum Wheat yield ET efficiency efficiency

Reference 1990-91 1991 -92

Under-irrigation 1990-91

Low frequency 1990-91 1991 -92

.o0 1.00 86.6 71 .O ' 34.4 50.3 47.4 67il

.o0 1.00 85.9 61.5 35.6 47.5 50.3 63.5

.o0 1.00 89.3 86.6 35.7 56.7 48.6 74.0

.o0 1.00 86.6 87.5 37.4 50.8 53.1 64.7

.o0 1.00 89.7 79.6 36.0 54.0 48.9 68.0 1 991 -92 1.00 0.99 87.2 78.6 40.7 46.5 52.7 59.0

4.4.2 Long-term Scenarios

The long-term scenario studies (1990-91 to 2010-2011) were carried out in order to predict long- term trends of soil salinity and crop yield under current and improved practices. The annual complete cycle for the year 2000-2001 and 2010-2011, comprising of sorghum and wheat crops in the sequence, have been considered for analysing and discussing the results obtained after 10 and 20 years of simulation. The data in Table 12 show that the relative yield of both crops is not affected by under-irrigation or low frequency irrigation scenarios. The higher values of relative ET, transpiration efficiency and ET efficiency are obtained when 20% less water is applied either through under-irrigation or low frequency irrigation compared with reference scenario. .

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’ Table 12. Plant response indicators under different long-term scenarios

Scenarios Relative yield

Sorghum Wheat Reference 2000-01

2010-11 . 1.00 1.00

Under-irrigation 2000-01 1.00 1.00

2010-1 1 1.00 1.00

Relative ET

Transpiration eff iciencv

Sorghum Wheat 85.6 72.0

84.9 64.5

90.3 86.6

87.6 88.5

Sorghum Wheat 35.4 51.3

36.6 48.5

36.7 57.7

38.4 53.8

Evapotranspiration efficiency

Sorghum Wheat

66.7

Low frequency 2000-01 1.00 0.99 89.7 78.6 37.0 55.0 49.9 69.0

201 0-1 1 1.00 0.99 87.2 79.6 39.7 47.5 53.7 62.0

From 1990-1991 to 2000-2001, the salt storage in the profile increased tÒ19.3 mg/cm“ (1.93 t/ha) in reference scenario compared to 29.7 and 29.1 mg/cm3 (2.9 t/ha) in case of under irrigation and low frequency irrigation (Table 13). During the 20 years (2010-2011), no salt build-up in the profile under reference scenario is indicated as salt storage value is -52.5 mg/cm2. In other two scenarios (under or low frequency irrigation), the salts build-up are very less (2.9 and 1.7 mg/cm2, respectively). Soil salinity values in all the scenarios are less than 4 dS/m. It indicated that irrigation with 20% less water as compared to farmers practice, can be successfully utilised without any deterioration in land productivity.

Table 13. Salt and water balance under different long-term scenarios

Scenarios P(cm) Ip(cm) Tact (cm) E,,, (cm) DW (cm) DS (mgkm*) Q,, (cm)

Reference 2000-01 65.1 60 46.4 26.5 -0.01 19.3 -49.0

2010-11 60.9 60 43.5 22.8 -5.86 -52.5 -45.8 Under-irrigation 2000-01 65.1 48 46.5 26.6 -0.2 29.7 -37.0

2010-11 60.9 48 42.3 24.9 1.5 2.9 -38.0 Low frequency 2000-01 65.4 48 46.4 26.4 -0.10 29.1 -37.1

2010-11 60.9 48 42.1 24.6 1.5 1.7 -38.3


In shallow water table areas, it is possible to reduce the water requirement of crops since a part of the water requirement can be met from the shallow water table. In the study area, a water of 4-5 dS/m salinity could be ,applied for pre-irrigation. This recommendation needs to be further tested for other agro-climatic conditions.

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SWAP is a powerful tool to test various alternate management options for planning purposes in the irrigation commands of India. A more rigorous testing of the model is underway at several locations in India. It is believed that based upon the outcome of these studies, firmer recommendations would emerge upon the full potential of this model for its application in India.

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